tbuckley/cabot-search huggingface dataset:
Abstract 4495: A mechanistic study of the TFE3-splicing machinery gene fusions reveals a new druggable target for translocation renal cell carcinoma
Authors: Nur Damayanti, Sabrina Orsi, Ricardo Cordova, Christopher Rupert, Li Shen, William Marston Linehan, Kirk Staschke, Peter Hollenhorst, David Heppner, Roberto Pili
Journal: Cancer Research (2023)

Abstract TFE3 is a member of basic helix-loop-helix leucine zipper MiT transcription factor family and its chimeric proteins are associated with translocation renal cell carcinoma (tRCC). Despite the variety of genes fusions, most of TFE3 fusions partner genes are linked to spliceosome machinery. Dissecting the function of TFE3 fused to spliceosome machinery factors (TFE3-SF) could direct the development of effective therapies for this lethal disease, which is refractory to standard treatments for kidney cancer. Here, by using a combination of in silico structure prediction, molecular cloning, next generation transcriptomics, FRET technology, mutagenesis, proteomics, and high-throughput high-content screening (HTHCS) we interrogated a series of oncogenic mechanisms of TFE3-SF-containing fusions, including spontaneous nuclear translocation, nuclear paraspeckle occupancy, enhanced in vitro proliferation and in vivo growth, transcriptome remodeling, alternative splicing reprogramming, and novel dimer partner recruitment. Molecular inhibition of TFE3-SF dimerization reverses its oncogenic activity and represents a potential new target for therapeutic intervention. By using HTHCS combined with FRET technology we screened FDA approved drugs library (LOPAC) and small molecule library (Microsource) and identified hits compounds which inhibit TFE3-SF dimerization. Hits compounds were validated in 2D and 3D models utilizing patient derived xenolines expressing TFE3-SF. Ouabain and terfenadine demonstrated decreased cell proliferation, reduced spheroid growth and in vivo tumor growth. Overall, our results unmask synthetic vulnerabilities of TFE3-SF dimerization for novel therapeutic strategies in patients with this aggressive type of kidney cancer. Citation Format: Nur Damayanti, Sabrina Orsi, Ricardo Cordova, Christopher Rupert, Li Shen, William Marston Linehan, Kirk Staschke, Peter Hollenhorst, David Heppner, Roberto Pili. A mechanistic study of the TFE3-splicing machinery gene fusions reveals a new druggable target for translocation renal cell carcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4495.
Abstract 1682: Bridging gaps in treatment resistance 2D models with the incorporation of 3D models
Authors: Manasa Gadde, Elizabeth Schwabe, Kshithija Mulam, Lindsay Hill, Christopher Bulow
Journal: Cancer Research (2023)

Abstract Introduction: 3D cellular models have become of increasing interest in anti-cancer drug discovery as a bridge between clinical models and traditional in vitro methods. An important component of this research is the comparison of drug-to-cell interactions and morphological characteristics between cells in mono-layer culture and the cells in 3D spheroids. Materials and Methods:The ResCu system is a novel long term, physiologically relevant culture system that avoids the need for passaging. It propagates tumoroids in a microenvironment that resembleshuman tissue. Cells with KRAS G12C mutation were cultured in the ResCu system for three months, during which they were constantly exposed to G12C inhibitors (G12Ci) for the evolution of resistant cell populations. Cells were also cultured in traditional 2D cultures and exposed to G12Ci. Transcriptomics was performed to determine resistant networks and identify different resistant subclones in each group. Results: We applied the ResCu system to model clinical resistance. We captured 95% of clinically identified on-target and pathway bypass resistance changes, and in the 2D system, only a fraction of mechanisms were discovered. Additionally, we noticed certain cell populations could tolerate higher doses of the G12Ci after resistance evolution in ResCu compared to 2D. A few had similar responses suggesting that the origin of the cell line plays a role in the microenvironment's impact on cellular response. Conclusion: By comparatively analyzing resistance evolution data for KRAS G12Ci in traditional 2D and ResCu, we were able to collect physiologically relevant data that can more confidently be applied to clinical studies than mono-layer cell culture data alone. Citation Format: Manasa Gadde, Elizabeth Schwabe, Kshithija Mulam, Lindsay Hill, Christopher Bulow. Bridging gaps in treatment resistance 2D models with the incorporation of 3D models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1682.
Abstract 6572: A lung cancer cell line explorer
Authors: Ling Cai, Luc Girard, Ralph DeBerardinis, Guanghua Xiao, John Minna, Yang Xie
Journal: Cancer Research (2023)

Abstract Over 300 lung cancer cell lines have been established in the past few decades with clinical annotations. Efforts from multiple institutions comprehensively profiled these cell lines for their genetic and epigenetic variations, gene and protein expression, metabolism, and functional liabilities. These data provide an unprecedented opportunity to accelerate lung cancer research. We developed a lung cancer cell line explorer at https://lccl.shinyapps.io/LCCL/ integrating over 35 datasets. We also incorporated engineered features such as pathway enrichment scores from copy number-denoised transcriptomic data and neuroendocrine scores. Our web application allows users to 1) query and download the processed datasets, 2) assess data reproducibility across studies, 3) review genomic abnormalities, 4) perform ad hoc bivariate analyses with the option to add filtering or coloring by a third feature, 5) generate heatmaps and correlation maps, 6) perform global association test to screen for significant association between a feature of interest and all features from a dataset of interest, and 7) upload their own datasets to be analyzed in conjunction with our in-house datasets. In summary, this online tool will greatly facilitate the utilization of high-dimensional datasets that characterize lung cancer cell lines. Citation Format: Ling Cai, Luc Girard, Ralph DeBerardinis, Guanghua Xiao, John Minna, Yang Xie. A lung cancer cell line explorer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6572.
Abstract 4517: Novel prognostic and predictive biomarker for neuroblastoma
Authors: Dinesh Babu Somasundaram, Zhongxin Yu, Ashley Baker, Natarajan Aravindan
Journal: Cancer Research (2023)

Abstract Recently we showed that Retinal degeneration protein 3 (RD3) is constitutively expressed in healthy adult and fetal tissues beyond retina and, its gradient expression from high to low in ganglioneuroma, ganglioneuroblastoma and neuroblastoma (NB). Crucially, our sequential in vitro and in vivo studies identified that RD3 regulates NB progression and metastasis, and its loss prompts the evolution of therapy defying progressive disease (PD). Here we investigated the prognostic significance of RD3 in NB, its predictive benefit and, its association to clinical outcomes. RNA-Seq data mining (4 independent study cohorts, total n = 1013) indicated that high RD3 can predict good NB prognosis. RD3 expression (immunohistochemistry) gauged in our NB patient cohort (n = 100) showed a positive correlation with longer overall survival (OS, P = 1.0E-04) and relapse-free survival (RFS, P = 2.1E-02). Similarly, high RD3 correlated with longer OS (P = 1.2E-03) and RFS (P = 2.1-02) in children presented with high-risk NB (HR-NB), irrespective of MYCN amplification status (MYCN amplified, P = 1.4E-02; non-amplified, P = 5.5E-03) and patient age (&amp;lt;2Y age, P = 2.8E-02; &amp;gt;2Y age, P = 1.0E-04) groups. Significantly, we observed a gradient loss of RD3 with NB progression, from stage 1 through stage 4 disease. Consistently, RD3 loss was substantial in metastatic disease when compared to the primary neuroblastomas, and this loss associated with poor OS in patients presented with metastatic disease (P = 4.0E-02). More importantly, RD3 is significantly lost in therapy resistant progressive NB and corroborated significantly (P = 9.5E-03) with the poor progression free survival. Multivariate analysis identified RD3 as an independent (P = 4.4E-02) prognostic factor for NB. These results demonstrate that RD3-loss can forecast poor prognosis in NB, and further imply that assessing RD3 loss could serve as the good predictor for therapy response and/or PD evolution. Together, these data identify a novel prognostic and predictive factor for neuroblastoma. Funding: This work was partially or in full, funded by Oklahoma Center for the Advancement of Science and Technology, OCAST-HR19-045; National Institutes of Health, NIH-P20GM103639 and Department of Defense DoD-CA210339 Citation Format: Dinesh Babu Somasundaram, Zhongxin Yu, Ashley Baker, Natarajan Aravindan. Novel prognostic and predictive biomarker for neuroblastoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4517.
Abstract 466: A potential pro-oncogenic role of SERPINB4 in melanoma
Authors: Gagan Chhabra, Carl A. Shirley, Rachel K. Robarge, Hassan A. Rizvi, Mary A. Ndiaye, Nihal Ahmad
Journal: Cancer Research (2023)

Abstract Despite recent therapeutic advancements, melanoma remains one of the deadliest forms of skin cancer. Melanoma metastasis and recurrence is associated with the existence of heterogeneous cell populations within tumors that have the ability to both initiate metastatic programs and bypass immune recognition. Tumor cells achieve immune evasion by interfering with immune signaling to limit immune cell infiltration, allowing tumor cell proliferation and growth. SERPINB4 (Squamous Cell Carcinoma Antigen 2 or SCCA2), a serine protease inhibitor, has been shown to regulate the host immune response against tumor cells by inhibiting immune cell activity. Interestingly, certain cancer cell types have been reported to overexpress SERPINB4. However, the expression profile and the functional significance of SERPINB4 in melanoma is not known. In this study, employing ‘The Cancer Genome Atlas’ (TCGA), we found that SERPINB4 is overexpressed and significantly associated with lower overall survival in patients with melanoma. Next, employing a panel of human melanoma cell lines, we demonstrated that SERPINB4 is overexpressed in melanoma cells when compared to normal human melanocytes. In addition, CRISPR knockout of SERPINB4 in high-SERPINB4-expressing A375 melanoma cells resulted in a significant decrease in proliferation of melanoma cells in comparison to control cells. Conversely, forced overexpression of SERPINB4 in low-SERPINB4-expressing SK-MEL-2 and SK-MEL-28 melanoma cells significantly increased melanoma cell proliferation. Moreover, RT-qPCR analyses suggested that SERPINB4 overexpression significantly increased, while its knockout significantly decreased epithelial-mesenchymal transition (EMT) markers (N-cadherin, β-catenin, Snail and Zeb1) in melanoma cells. Additionally, SERPINB4 manipulation significantly modulated the expression of genes involved in antigen-presentation (MHC Class I molecules, HLA-A, -B, and -C) in melanoma cells. Taken together, our data suggested a potential oncogenic role of SERPINB4 in melanoma. Our study also suggested that SERPINB4 might be a promising therapeutic target for melanoma. Indeed, additional in vitro mechanistic and in vivo studies are needed to firmly establish the mechanism and therapeutic potential of SERPINB4 for melanoma management. Citation Format: Gagan Chhabra, Carl A. Shirley, Rachel K. Robarge, Hassan A. Rizvi, Mary A. Ndiaye, Nihal Ahmad. A potential pro-oncogenic role of SERPINB4 in melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 466.
Abstract 3636: Liver endothelium secreted LRG1 promotes metastatic colorectal cancer growth through the HER3/RSK/EIF4B AXIS
Authors: Moeez Ghani Rathore, Michelle Wright, Wei Huang, Derek Taylor, Yamu Li, Jordan Winter, Zhenghe Wang, John Greenwood, Stephen Moss, Rui Wang
Journal: Cancer Research (2023)

Abstract Background: 25% of patients diagnosed with colorectal cancer (CRC) have liver metastasis at presentation, and ~80% of all metastatic CRC are developed in the liver. We previously reported that liver endothelial cells (ECs), a key component of the liver microenvironment, secrete LRG1 to promote CRC growth via activating human epidermal growth factor receptor (ERbB3, also known as HER3). However, we found that LRG1-induced HER3 activation is distinct from the canonical neuregulin 1 (NRG1)-induced HER3 pathway. The present study further validated LRG1 as a new HER3 ligand for promoting mCRC growth and elucidated the novel downstream signaling pathway induced by LRG1-HER3. Methods: We first measured the binding affinity between HER3 and LRG1 by Biolayer interferometry (BLI). We then used in vitro and in vivo xenograft approaches to determine the effect of LRG1 monoclonal antibody (15C4) on HER3 activation and CRC growth. To further determine the role of LRG1 in promoting CRC growth in the liver, we used murine CRC cells in a syngeneic orthotropic liver injection model to establish CRC allografts in the liver of LRG1−/− mice with systemic LRG1 knockout and wild-type siblings (LRG1+/+). We also performed unbiased phospho-MS analysis and subsequent validations to determine the downstream signaling pathway activated by LRG1-HER3. Results: We identified that LRG1 binds to HER3 with the affinity at ~100nM. The LRG1 antibody 15C4 completely attenuated LRG1-induced HER3 activation and in vitro and xenograft growth in vivo. Moreover, LRG1−/− mice with CRC allografts in the liver had 2 times longer overall survival than tumor-bearing LRG1+/+ mice. Lastly, unbiased -omics analysis identified eIF4-protein synthesis is significantly activated by LRG1. With target-specific inhibitors, we further determined that LRG1-HER3 activates the PI3K-PDK1-RSK1/3-eIF4 axis independent of AKT. Conclusions: We identified LRG1 as a novel HER3 ligand and demonstrated that the liver microenvironment-derived LRG1 plays a key oncogenic role in mCRC, by activating a novel RSK-eIF4 survival pathway. Our findings highlighted the potential of blocking LRG1-HER3 and involved downstream pathways for treating patients with mCRC. Citation Format: Moeez Ghani Rathore, Michelle Wright, Wei Huang, Derek Taylor, Yamu Li, Jordan Winter, Zhenghe Wang, John Greenwood, Stephen Moss, Rui Wang. Liver endothelium secreted LRG1 promotes metastatic colorectal cancer growth through the HER3/RSK/EIF4B AXIS. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3636.
Abstract 4822: Signaling pathways associated with stress factors in gastrointestinal cancers
Authors: Amayrani Sanchez, Kyle D. Doxtater, Samantha Lopez, Sophia Leslie, Elias George, Vijian Dhevan, Meena Jaggi, Subhash Chauhan, Manish K. Tripathi
Journal: Cancer Research (2023)

Abstract Gastrointestinal (GI) cancer affects various significant organs along the gastrointestinal tract, which contains several of the leading cancer-related deaths in the United States. According to the American Cancer Society, colorectal and liver cancers are among the top ten leading deaths due to cancer, ranking third and sixth, respectively. In the Rio Grande Valley region with a majority Hispanic population, colorectal cancer and liver have a higher occurrence than in the entire state of Texas. However, for many, a cancer diagnosis can worsen with stress, which is also a common occurrence within the Rio Grande Valley region due to 30% of its population living in poverty. Stress can cause changes to the immune system's functionality and the inflammatory response that could lead to insufficient surveillance for any potential oncogenicity. When the Hypothalamic-Pituitary-Adrenal (HPA) axis becomes activated by stress, it will release several stress hormones, such as leptin and cortisol, in response that can play a role in the progression and growth of cancer tumors. To further explore this relationship, hepatocellular carcinoma (HCC) cells and colorectal cancer (CRC) cells were treated with cortisol and leptin at various time points to create models mimicking acute and chronic stress exposure. Afterward, the mRNA mean fold change levels were obtained utilizing the RT-PCR method to determine the levels of each gene in various liver and colorectal cancer cell lines.Additionally, a kinase assay will provide further insight and evidence into the signaling pathway based on the results of the RT-PCR. The current results have shown an upregulation of lncRNA MALAT1, ZNF384, and YB-1 genes at varying degrees depending on the cell line, stress hormone, and duration of treatment. Consequently, these findings have shown an upregulation of oncogenic long non-coding RNA and transcription factors, presenting a signaling oncogenic pathway model by stress factors in HCC and CRC cell lines. Therefore, understanding the role of stress-factors in the oncogenicity and progression of cancer can aid in creating therapeutics for a population where stress can play a role in cancer disparity. Citation Format: Amayrani Sanchez, Kyle D. Doxtater, Samantha Lopez, Sophia Leslie, Elias George, Vijian Dhevan, Meena Jaggi, Subhash Chauhan, Manish K. Tripathi. Signaling pathways associated with stress factors in gastrointestinal cancers. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4822.
Abstract 4308: Cancer as a disease of information
Authors: Adam Julian Goldstein
Journal: Cancer Research (2023)

Abstract The causes and symptoms of cancer are often described in physical terms, for example as DNA mutations leading to increased cell proliferation. These understandings have been immensely informative, but physical changes are only one of several ways to understand what cancer is and why it behaves the way it does. An alternative perspective builds upon Claude Shannon's work in information theory, and sees cancer as a result of missing, noisy, and/or distorted information. In this talk I summarize existing research and discuss the implications for understanding cancer as a disease of information. I then explain how detecting and treating cancer look different when viewed through this lens. In particular, I discuss how this approach offers the hope for rehabilitating cancer cells by restoring expected information flows, in contrast to some current treatments which exacerbate information disruptions. Citation Format: Adam Julian Goldstein. Cancer as a disease of information. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4308.
Abstract 4375: A bootstrapping method to optimize go/no-go decisions from single-arm, signal-finding studies in oncology
Authors: Aparna Mohan, Raunak Dutta, Jacqueline Buros-Novik, Omobolaji Akala, Brian Gregory Topp
Journal: Cancer Research (2023)

Abstract Background: Phase Ib, single-arm trials are common in oncology development. Since these trials are not powered for statistical significance, Go/No-Go decisions are largely driven by observed trends in ORR relative to historic control. Here we develop a bootstrapping method to systematically compare secondary endponts, such as the waterfall plot, to historic control data. In addition, we identify an actionable Go threshold and estimate the expected false positive and false negative rates associated with that threshold. Method: A proprietary mathematical model was used to simulate thousands of single-arm trials (n = 30) with a combination of pembrolizumab and a novel agent with miserable (Rx0), modest (Rx1), moderate (Rx2) or magnificent (Rx3) efficacy. A bootstrapping method was used to compare waterfall plots from these trials to a simulated Phase III pembrolizumab monotherapy control arm (n = 511). Results: The bootstrapping method provides a visualization of the observed waterfall plot for the single-arm combination trial relative to the range of possible outcomes from historic control data (5th, median, 95th percentile). The method also provides a score reflecting the probability that the observed data is different from the historic control. An ROC analysis showed a strong ability to separate drugs with modest (AUROC = 83%), moderate (AUROC = 96%) and magnificent combination efficacy (AUROC = 99%) from drugs with miserable efficacy. The method was shown to effectively move drugs with a range of efficacy through an in-silico pipeline while rejecting drugs without combination efficacy. Conclusion: This bootstrapping method allows comparisons of secondary endpoints from early clinical trials to historic control data. The visualization is intuitive, and the quantification provides an actionable Go-threshold. The method also provides an estimate of the risk associated with that recommendation. We suggest incorporation of this as a component of Go/No-Go decision making in early oncology trials. Citation Format: Aparna Mohan, Raunak Dutta, Jacqueline Buros-Novik, Omobolaji Akala, Brian Gregory Topp. A bootstrapping method to optimize go/no-go decisions from single-arm, signal-finding studies in oncology. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4375.